#### How do I cite the EnergyFlow package?

@article{Komiske:2017aww,
author         = "Komiske, Patrick T. and Metodiev, Eric M. and Thaler, Jesse",
title          = "{Energy Flow Polynomials: A complete linear basis for jet substructure}",
journal        = "JHEP",
volume         = "04",
year           = "2018",
pages          = "013",
doi            = "10.1007/JHEP04(2018)013",
eprint         = "1712.07124",
archivePrefix  = "arXiv",
primaryClass   = "hep-ph",
reportNumber   = "MIT-CTP-4965"
}

@article{Komiske:2018cqr,
author         = "Komiske, Patrick T. and Metodiev, Eric M. and Thaler,
Jesse",
title          = "{Energy Flow Networks: Deep Sets for Particle Jets}",
year           = "2018",
eprint         = "1810.05165",
archivePrefix  = "arXiv",
primaryClass   = "hep-ph",
reportNumber   = "MIT-CTP 5064",
}


#### Why Python instead of C++?

Computing the energy flow polynomials requires a function such as NumPy's einsum that can efficiently evaluate arbitrary tensor contractions. To write such a function from scratch in C++ is difficult, and there is no obvious library in C++ to use (though if one were to attempt this the tensor algebra compiler seems like a promising tool).

NumPy is a highly-optimized Python library written in C that provides all of the tools required to efficiently compute the energy flow polynomials. Libraries like NumPy take advantage of optimizations that the physicist-programmer typically does not, such as architecture-optimized libraries like BLAS or LAPACK and low-level features such as SSE instructions.

#### Can I contribute to the code?

All of our code is open source and hosted on GitHub. We welcome additional contributors, and if you are interested in getting involved please contact us directly. Contact information is included in the relevant Energy Flow papers and our GitHub repository.

#### How do I report an issue?

Please let us know of any issues you encounter as soon as possible by creating an Issue on the EnergyFlow GitHub repository.

#### Where can I get graph image files?

Image files for all connected multigraphs with up to 7 edges in the energy flow polynomial style are available as pdf files here. You are free to use them with the proper attribution.